Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for capturing the presence of radio frequency (RF) transmitting devices comprising: collecting, using at least one sensor, RF data in one or more spectrums associated with the devices; extracting metadata properties; determining transmitting device information; logging session and device properties for each device detected; and exporting at least a portion of data collected and or logged.
2. The method of claim 1 wherein the collected RF transmissions have no predetermined size.
A system and method for processing radio frequency (RF) transmissions of variable size in a wireless communication environment. The technology addresses the challenge of efficiently handling RF signals that do not conform to fixed packet or frame sizes, which can occur in dynamic or unstructured communication scenarios. The method involves collecting RF transmissions without imposing a predetermined size constraint, allowing for the capture of signals that may vary in length due to factors such as environmental interference, transmission errors, or adaptive modulation techniques. The collected transmissions are then processed to extract relevant data, which may include decoding, error correction, or signal analysis. The system may further include components for filtering, amplifying, or converting the RF signals into a usable format. By accommodating variable-sized transmissions, the method ensures robust performance in environments where signal integrity or transmission conditions are unpredictable. This approach is particularly useful in applications such as cognitive radio, software-defined radio, or other systems requiring flexible signal processing. The method may also include steps for dynamically adjusting processing parameters based on the characteristics of the incoming RF transmissions to optimize performance.
3. The method of claim 1 further converting the collected RF data into data frames.
A system and method for processing radio frequency (RF) data involves collecting RF signals from a target environment using one or more RF sensors. The collected RF data is then converted into data frames for further analysis. The data frames may include time-stamped samples of the RF signals, allowing for structured processing and interpretation. The system may also involve preprocessing the RF data to remove noise or interference before conversion into data frames. The data frames can be used for various applications, such as spectrum analysis, signal detection, or environmental monitoring. The method ensures that the RF data is organized in a structured format, facilitating efficient storage, retrieval, and analysis. The system may also include a processing unit that performs the conversion and preprocessing steps, along with a storage unit for retaining the processed data frames. The method may further involve transmitting the data frames to a remote server or device for additional processing or visualization. The system is designed to handle high-frequency RF signals and can be deployed in various environments, including urban, rural, or industrial settings. The method ensures accurate and reliable conversion of RF data into a structured format, enabling real-time or batch processing for different applications.
4. The method of claim 1 further comprising extracting metadata through applying frame format.
A system and method for processing video data involves extracting metadata from video frames by applying a frame format. The technology operates in the domain of video analysis, addressing the challenge of efficiently extracting structured metadata from raw video data to enable advanced applications such as content indexing, object recognition, and automated tagging. The method includes capturing video frames from a source, such as a camera or stored video file, and analyzing the frames to identify key features. These features may include temporal information, spatial data, or other attributes relevant to the video content. The system then applies a predefined frame format to the extracted features, converting them into a standardized metadata structure. This metadata can include timestamps, frame dimensions, color profiles, motion vectors, or other descriptive data. The frame format ensures consistency and compatibility with downstream processing systems, allowing for seamless integration with databases, analytics tools, or machine learning models. By automating metadata extraction, the system enhances the efficiency of video processing workflows, reducing manual effort and improving accuracy. The method supports real-time or batch processing, making it adaptable to various use cases, including surveillance, media production, and automated content moderation. The extracted metadata can be stored, transmitted, or used to generate insights, such as identifying patterns or anomalies within the video data.
5. The method of claim 1 further using system logic based at least in part on extracted device metadata.
A system and method for processing device metadata to enhance device management and functionality. The technology addresses the challenge of efficiently extracting and utilizing metadata from devices to improve system operations, such as device identification, configuration, and troubleshooting. The method involves collecting metadata from devices, which may include hardware specifications, firmware versions, network configurations, and usage patterns. This metadata is then analyzed to extract relevant information, such as device capabilities, performance metrics, and operational status. The extracted metadata is used by system logic to make decisions, such as optimizing device performance, automating configuration tasks, or detecting anomalies. The system may also correlate metadata from multiple devices to identify trends, predict failures, or recommend maintenance actions. By leveraging device metadata, the system enables more intelligent and automated device management, reducing manual intervention and improving overall system efficiency. The method may be applied in various domains, including IoT networks, industrial automation, and IT infrastructure management, where device metadata plays a critical role in maintaining system reliability and performance.
Unknown
December 3, 2019
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